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New laws offer nuclear industry incentives for existing power plant uprates
This year, the U.S. nuclear industry received a much-needed economic boost that could help preserve operating nuclear power plants and incentivize upgrades that extend their lifespan and power output.
Signed into law in 2022, the Inflation Reduction Act offers production tax credits (PTCs) for existing nuclear power plants and either PTCs or investment tax credits (ITCs) for new carbon-free generation. These credits could make power uprates—increasing the maximum power level at which a commercial plant may operate—a much more appealing option for utilities.
Takanobu Kamei, Tadashi Yoshida
Nuclear Science and Engineering | Volume 84 | Number 2 | June 1983 | Pages 83-97
Technical Paper | doi.org/10.13182/NSE83-1
Articles are hosted by Taylor and Francis Online.
In the design of a large liquid-metal fast breeder reactor (LMFBR), the bias-factor method is usually applied to reduce the error of predicted values of neutronics parameters. These bias factors are obtained through the analysis of mock-up experiments. When there exist some differences between the reactor to be designed and its mock-up experimental system, it is impossible to be free from extrapolation errors even after the application of the bias factor. This paper presents an evaluation model for the above kind of extrapolation error, which still remains after the biasing, due to cross-section uncertainties. As an example of an application of this model, the extrapolation error of the design parameters of a 1000-MW(electric) fast breeder reactor was evaluated for the case where bias factors from the large LMFBR mock-up critical experiment, ZPPR-10D, were available. As a result, the error in keff was found to range 0.3 to 1.1% depending on how precisely the reactivity effect of higher plutonium isotopes (especially 241Pu) was predicted. The extrapolation error was predicted to be <2.5% for the control rod worth and also for the fission rate distributions of 239Pu and 238U. It was also shown that the extrapolation error for the control rod worth was reduced by use of a bias factor constructed from some different rod patterns.